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Record W3183072914 · doi:10.3389/fpsyg.2021.686262

Empathetic Factors and Influences on Physical Performance: A Topical Review

2021· review· en· W3183072914 on OpenAlexafffund
David G. Behm, Tori B. Carter

Bibliographic record

VenueFrontiers in Psychology · 2021
Typereview
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEmpathyPsychologyFeelingAffordanceAffect (linguistics)Social psychologyAssociation (psychology)Cognitive psychologyDevelopmental psychologyCommunication

Abstract

fetched live from OpenAlex

Performance is dependent upon both physical and psychological factors. As a social animal, human behaviors are influenced by interactions with others. Empathy is based on social interactions and is defined as the understanding, awareness of, sensitivity to, and ability to vicariously experience the feelings, thoughts, and experience of another. There are few investigations on the influence of empathy in relation to individual and team performance and activity. There is some initial research suggesting that observing sad photos or videos or fatiguing exercise can adversely affect subsequent performance. Possible mechanisms may be attributed to mirror neurons or the affordance competition hypothesis. The relative degree of empathetic influences can be modulated by sex, age, personal familiarity, cultures and other factors. With the limited research in sport and exercise science, there is a need for more research to investigate the role of empathy on individual and team performances. The objective of this topical review was to examine the possible effects of empathy on physical performance, the potential underlying mechanisms and influencing variables moderating the association between empathy and performance?

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.078
GPT teacher head0.421
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2021
Admission routes2
Has abstractyes

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